Anthropometrics and development in Twentieth-century Spain: cohort
trends and spatial patterns of height and robustness
Antonio D. Cámara1
Joan García Román2
Abstract
This paper seeks new insights concerning the relationship between environmental conditions and
the anthropometric measures of a population. We analyze cohort trends and spatial patterns of physical
robustness (height, weight and chest circumference) during the process of economic development in
twentieth-century Spain. The data were drawn from Spanish Military Statistics that record male cohorts
from 1934 to 1973. Dramatic socioeconomic and demographic changes occurred during that period and
consequently the life course of those cohorts witnessed very diverse environmental contexts. Time-cohort
series and anthropometric cartography are presented and discussed in light of supplementary data on GDP
and infant mortality.
Our results show convergence in height and robustness across Spanish regions. This process was
especially intense among cohorts born during the 1950s and the 1960s. Spatial patterns—primarily tallrobust North-Eastern regions and short-weak Central-Southern regions—of development persisted at least
until the 1990s (cohorts born during the 1970s). These patterns are only partly associated to economic
disparities and there are also remarkable discrepancies between height and robustness patterns which
moderates conclusions on the evolution of living conditions exclusively approached by height.
1
2
Corresponding author. Centre d’Estudis Demogràfics. [email protected]
Departament de Geografia. Universitat Autónoma de Barcelona. [email protected]
1
Introduction and aims
Spain attained high development levels over the twentieth century as a result of
intense economic and demographic changes (Nadal et al., 1987). These changes are
reflected through diverse indicators. It is estimated that production multiplied by 8.2
between 1930 and 2000 whereas population increased by a factor of only 1.7. Therefore
per capita GDP was multiplied by 4.7 which would yield an annual per capita growth
rate of 2.2 percent (Alcaide, 2003).
Life expectancy at the turn of the century was hardly 35 years3; fifty years later, in
1950, it had risen to 62 years and in 2000 it was about 79 ranking among the highest in
the world (INE, 1991, 2007).
Adult height, considered an indicator of the net nutritional status as explained in
the next section of this paper, also illustrates the intensity of these changes. Spaniards
born during the 1970s were about 9 cm taller on average (males) and 6 cm (females) than
those born during the first decades of the twentieth century (Spijker et al., 2012)4.
A composite measure of well-being, the Human Development Index (HDI), that
combines three basic dimensions of human development (health, education and income)
was estimated to be 0.363 in 1900 (Escudero and Simón, 2003) and 0.839 in 2000 (IHDI,
online)5.
These trends in economic and bio-sanitary indicators imply that the current
Spanish population had very diverse life courses: from cohorts who experienced cycles of
hardships and severe deprivation to those who grew up in an affluent society.
3
In 1900 life expectancy in other European countries was: 32.4 years in Russia, 42.8 years in Italy, 44.4
years in Germany, 47.4 years in France, 48.2 years in the UK, 49.9 years in the Netherlands and 54.0 years
in Sweden (Livi-Bacci, 1992).
4
By contrast the mean height among Spanish males simply increased from 162 cm to 163 cm among
cohorts born during the second half of the 19th century (Gómez-Mendoza and Pérez-Moreda, 1985;
Cámara and García-Román, 2010; a collection of recent essays in English on Spanish anthropometric
history, in Martínez-Carrión, 2009). These figures set Spain among the shortest nations in Europe. Results
from works collected by Crafts (1997: 628) show the following male height figures (they have been
rounded for simplicity purposes) among cohorts born by the middle of the 19th century: 168 cm (Sweden),
167 cm (Austria), 166 cm (Denmark), 165 cm (United Kingdom and France), 164 cm (Germany) and 162
cm (Italy). Among cohorts born between 1950 and 1959 the mean male height were approximately 172 cm
in Spain, 176 cm in Germany, 178 cm in Denmark, 179 in the Netherlands, 176 cm in Britain and 173 cm
in France (Spijker et al., 2008; Hatton and Bray, 2010). The gap remained large until the last decades of the
20th-century.
5
The scale of HDI is 0-1. A value of 0.8 is usually accepted as indicative of a high development whereas
values under 0.5 are indicative of low development.
2
Aside from this generational contrast, Spain was a country of strong
socioeconomic and demographic disparities during the 20th century. For instance, within
a context of intense economic growth during the central decades of that century both
population and non-agrarian economic activities tended to concentrate in the most
dynamic regions during the most expansive period of modern development in Spain and
other Western European countries (1950-75). This is vividly reflected by the increasing
weight of these regions (e.g. Madrid, Catalonia or the Basque Country) on the national
per capita GDP (Carreras, 1990).
Few indicators grant insights on both cohort and spatial implications of these
development processes given that most of them, including life expectancy, are based on
cross-sectional data. In words, spatial disparities reflected by these indicators do not
necessarily respond to the disparities in living conditions experienced over the life course
in those territories. Height data are usually of the same type (cross sectional) but have
properties that allow for both spatial and cohort interpretations.
The final height that one attains in adulthood is the result of two types of
determinants: 1) genetics establish a maximum potential for each individual and 2)
environmental factor determine to what extend that biological potential will be attained.
In consequence, within a genetically uniform population variations in height over time
and between subpopulations are mainly the result of environmental factors (e.g.
socioeconomic and epidemiological). Accordingly, many studies in the fields of human
biology and social sciences have underlined the strengths of height as an indicator of
living conditions for its capacity to summarize the balance between body energy inputs
and outputs during the physical growth process. There are two post-natal critical periods
for growth which are very sensitive to environmental stressors. These periods are infancy
(i.e. the two first years of life) and puberty (i.e. when the adolescent spurt occurs, prior to
the attainment of the adult final height) (Bogin, 1988; Tanner, 1989). A balanced net
result between inputs (quantity and quality of food intake) and outputs (energy
expenditure from basal metabolism, physical effort and exposure to illness) contributes to
a normal growth pattern (i.e. one attains the stature that is genetically inherited).
Oppositely, prolonged environmental stress during the growth cycle (e.g. chronic
3
malnutrition, child labor or a continuous exposure to illness) may alter that biological
pattern and may eventually result in loses from the potential height as an adult.
In this work the living conditions of Spanish male cohorts born during the central
decades of the twentieth century (1934-1973) are studied.6 Our main aim is the analysis
of the evolution of spatial disparities during the intense process of socioeconomic
development experienced by this country over that period. A combination of spatial and
cohort analysis is essayed that contributes to better establish the impact of environmental
conditions. Anthropometric measures for the study of the interaction between
socioeconomic processes and living conditions in a historical perspective are enhanced
since we track differences not only in height but also in robustness by including weight
and chest circumference (CC) in a robustness index.
Data
Time-cohort series and cartography are based on the charts from the Military
Statistics that were included in the Spanish Statistic Yearbooks. These charts summarize
the data from the individual records of the compulsory military service in Spain until
1996 (the last mandatory enlistment was in 1995). The charts present relative
distributions (i.e. percentages) of three anthropometric measures (stature in centimeters,
weight in kilograms and CC in centimeters). This information is provided in 5-unit
intervals both nationally and by regions. The yearbooks have been published in Spain
since the middle of the 19th Century but relatively few are valid for our purposes (Table
1). For instance some yearbooks only provide the percent of recruits that were excluded
due to shortness and also tabulation errors were detected in the data of the 19th century.
Some of aforementioned studies on Spain made partial use of the National
Military Statistics but they did not systematically exploit this source and certain
anthropometric measures provided were neglected.
6
In Spain, a number of studies based on military records have displayed a regional gradient of male
statures (Gómez-Mendoza and Pérez-Moreda, 1985; Quiroga, 1998; Gónzalez-Portilla, 1998 and 2001;
Martínez-Carrión, 2005). Gómez-Mendoza’s and Pérez-Moreda’s work analyzed male height in Spanish
regions in 1858. Martínez-Carrión’s work compared regional disparities in height in Italy and Spain in
1955 and 2000. Quiroga’s work presented regional series for cohorts born 1873-1934.
4
The birth year is not provided. We know that the age of enlistment was 21 years
in 1955 (first enlistment) and that no single cohort avoided the military service. In
consequence, birth years were scrolled from 1934 producing the cohort span 1934-74. In
order to obtain homogeneous cohort groups (i.e. 5-yr cohorts) the last cohort analyzed in
this work is 1973.
The format of the data remain quite constant but its representativeness decreased
since the beginning of the 1990s as the percent of young males that opted for the social
service alternative to military service increased. These individuals were not captured by
the military statistics and/or a varying percent of those who were enlisted were not
measured (the percent of missing cases is provided on Table A5 of the appendix). This
compels us to omit the results on CC and RI for the last cohort group that is analyzed in
this work (1969-73) as well as to moderate our statements on height and BMI of these
cohorts. For the same reason the cohort group 1964-68 was chosen to close the map
series.
We believe that these statistics included those recruits who did not scored the
minimum height required to enter the army as the lower interval in the distributions is
under that minimum height7. Also the percent potentially excluded for this reason was
very low (Figure 1). Note that the potential effects of rounding caused by the
measurements being recorded in half inch increments is smoothed across the intervals
since they all use the same convention. All of this leads us to believe that the resulting
averages are representative of the whole of the Spanish male population. This conclusion
has been tested by comparing these averages with those resulting from series based on the
crude height data collected from local archives that included short recruits. Our averages
fall solidly within the range of those obtained for different areas in Spain (Martínez
Carrión, 2009).
7
The minimum height required was established at 154 cm. in 1912 (Abella, 1915). Subsequents laws did
not establish a minimum height but rather an adequate proportionality between height, weight and CC.
5
Table 1
Summary of anthropometric information contained in the Spanish Statistic Yearbooks (19th-20th
centuries)
He ight
Enlistments
1
2
1992-95
9 (5)
<155
1987-91
1964-85
Weight
3
1
10 (5)
190+
9 (5)
185+
180+
7 (5)
1955-63
8 (5)
<150
1925-28
3 (7)
<163
1917-1924
3 (5-10)
1915-16
5 (2-5)
154
>171
1861
13 (3)
<147
>180
1859
10 (3)
<151
1858
10 (3)
<150
2
CC
3
1
10 (5)
90+
8 (5)
8 (5)
80+
<50
75+
2
3
105+
7 (5-6)
<75
>100
170+
1862-67
>175
Note: 1, number (and length) of intervals; 2, lower limit of the distribution; 3, upper limit of the distribution
Figure 1
Distributions by birth cohort
Height (cm)
Weight (kg)
CC (cm)
1964-68
40
35
30
25
%20
15
10
5
0
<75
75‐79
80‐84
85‐89
Chest circumference
90‐94
95‐99
Source: Own computations based on Military Statistics of Spanish Yearbooks
6
The data are provided by “anthropo-demographic” zones and regions (HoyosSainz, 1942)8. Regions are more convenient for our purposes since they better approach
(though not exactly) the current administrative structure of Spain (Figure 2).
Finally, although this is not specified in the source we believe that the data
classify recruits to their place of residence at the time of the anthropometric measurement
and not to their place of birth. The potential bias caused by this is discussed in the last
section of this paper.
Figure 2
Spanish regions
Current division (left) and anthropo-demographic regions (right)
Data on GDP and mortality were drawn from previous works and they were
treated to fit the anthropo-demographic regions as it is explained in the next section of the
paper. GDP data come from Alcaide’s estimates (2003). They are the most accepted and
8
The equivalence between the anthropodemographic regions and the current autonomous regions in Spain
is as follows (the current regions appear in brakets): Región Galaica (Galicia), región Cántabra (Asturias
and Cantabria), región Vasca (País Vasco), región Aragonesa-Riojana (Aragón, La Rioja and Navarra),
región Castellano-leonesa (Castilla-León) región Catalana (Catalunya and Illes Balears), región Levantina
(Comunitat Valenciana and Murcia), región Extremeño-manchega (Extremadura and Castilla-La Mancha)
and región Andaluza (Andalucia). Hoyos’ criterion results in some socioeconomic and cultural
discrepancies. For instance, the región Levantina includes the current autonomous regions Comunitat
Valenciana and Murcia. Per capita GDP was systematically higher in the former during the central decades
of the 20th century and Murcia was economically closer to the Southern region of Andalusia. Also most of
the region Comunitat Valenciana speaks Catalan, thus being culturally closer to the region Catalana.
Anthropometric zones were discarded because they were too broad for our purposes. For instance, the
Northern zone includes Asturias, Cantabria, País Vasco and Navarra.
7
one of the few available resources that include data on first half of the twentieth century
(Carreras et al. 2005). Some caution must guide the interpretation of the relationship
between this economic indicator and anthropometrics although we believe that the figures
from Alcaide reflect the patterns and trajectories of economic development in twentieth
century Spain in a very reasonable manner. Infant mortality rates were drawn from
Gómez-Redondo (1992).
8
Methods
Series and cartography of anthropometric measures are based on weighted
averages that were obtained by using the central value within each five-unit interval
across the distribution. Open intervals were assumed to have a length of five units. The
limits of open intervals varied (Table 1) but this does not substantially affect our results
since 1) their variations paralleled the trend over time and 2) the percents within these
open intervals remained very low. The averages that were obtained in that way were
compared to those occasionally provided in the Yearbooks. As both figures hardly
differed our own calculations were systematically used in order to homogenize the
information used to construct series and maps. Height, Body Mass Index (BMI) and
Robustness Index (RI) averages were computed on five-year cohort groups in order to
make our trends more robust. The average of 1955-1959 enlistments (cohorts 1934-38) is
made of three years because regional data are not provided in 1956 and 1957. The
average of 1970-1974 enlistments (cohorts 1949-53) is a three-year average (1970, 1973
and 1974). The years 1971 and 1972 were discarded because of the strong drop observed
in all three anthropometric measures. This may have to do with tabulation errors or, more
likely, with an earlier age at measurement. According to the military laws, from 1907 to
1968 the recruits were enlisted and measured at age 21 with the exception of the Civil
War (1936-39) and immediate postwar years. In subsequent years, the age at
measurement was 19 years and 18 years (1987).
BMI was computed as the mean weight divided by the square of the mean height.
To be noted about the components of this index, stature is a function of prior
environmental conditions but weight is partially related to both stature and short-term
environmental variations, e.g. illness (this short-term effect, nevertheless, is smoothed
when large populations are analyzed).
BMI 
Wkg
Hm
2
9
The categories commonly accepted for this index are underweight (<18.5 kg/m2),
normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2) and obesity (>30.0
kg/m2). These categories do not apply in this study because the range across regions is
not large enough (i.e. we will not find obese regions vs. underweighted regions since the
BMI of each region is comprised of many individuals who, obviously, tend to average a
normal weight). Therefore this indicator is mapped in intervals of 0.5 units9.
The Robustness Index (RI, also known as Pignet Index) results from subtracting
the weight and the CC to height.
RI  H cm  (Wkg  CCcm )
The interpretation of this indicator can be troublesome. RI may indicate different
things depending on the context. At present RI is a sort of fitness index (high values
indicate a good fitness). In this work the interpretation is the opposite. Lower scores
indicate a higher robustness: 0-10 (very strong); 11-15 (strong); 16-20 (good); 21-25
(intermediate); 26-30 (weak); 31-35 (very weak); +35 (pathologic problems)10. As with
BMI these categories do not apply here and we opted to map the results in 2-unit
intervals11. Interestingly, it will be found that relatively tall populations present relatively
low values of robustness as a result of very low values of weight and CC (i.e. weight does
not scale with height in these data as one would expect of healthy populations).
Per capita GDP and infant mortality data included are aimed at illustrating
development disparities across Spanish regions and potential discrepancies between
economic and biological components of well-being (per capita GDP comes from
Alcaide, 2003, and infant mortality rates come from Gómez-Redondo, 1992). Both
indicators required some manipulation to fit the anthropo-demographic regions. Mortality
rates were originally provided at the provincial level and had to be aggregated into
regions. As the provinces within any region differ in size, population and other
9
This lenght allows to capturing significant variations in mean BMI between cohort groups as well as
regional disparities. For instance, keeping weight constant at 60 kg, a 2 cm change in height (e.g. from 166
cm to 168 cm) makes BMI to decrease from 21.77 to 21.25.
10
Translation from Spanish is literally (Guillén-Rodríguez, online).
11
Keeping weight and CC constant at 60 kg and 80 cm respectively, a 2 cm. change in stature (from 1.66 to
1.68) leads to an increase from 26 to 28 in RI.
10
socioeconomic characteristics, the infant mortality rates had to be weighted. This was
done by using the live births recorded in each province. Data on live births were obtained
from the historical vital statistics of the Spanish Population (MNP) (INE; online).
GDP from Alcaide (2003) was available by region but occasionally several
regions needed to be merged to fit the anthropo-demographic regions. In those cases the
sum of GDPs and the sum of populations were utilized to compute per capita GDP.
As we work with five-unit birth cohorts, annual mortality rates by province were
averaged accordingly. Estimates on GDP were provided every five years by Alcaide so
that two GDPs were taken and averaged matching each cohort group and the same was
done with the populations that served as denominator of per capita GDP. More
specifically the values for population used in the computation were those at July 1st of a
given year and are also from Alcaide’s work. For instance, for any given region per
capita GDP associated to cohorts 1934-38 is an average of GDPs 1935 and 1940 divided
by the average of mid-year populations in 1935 and 1940.
Our results are a selection of materials. Some more detailed figures are included
in the appendix that closes this work and the rest are available from authors on request.
11
Results
The average stature of Spanish males increased about 9 cm (or 5.4 percent) from
166 cm among those born in 1934 to 175 cm among those born in 1973. This is an
increase of more than 2 cm per decade thus steeper than that observed in any other
western European country among the same cohorts (over the period 1951-1980 male
mean height progressed 2.53 cm per decade in Spain, whereas the mean increase in
Europe was estimated to be 1.26; Hatton and Bray, 2010). Among the aforementioned
cohorts the average weight increased from 62 kg to 69.4 kg (or 11.9 percent) and the
average CC did so from 87 to 89 cm (cohort 1968) (or 2.3 percent).
Both composite indexes, BMI and RI, do not display a consistent (i.e. uniform)
trend over time as a result of the changing relationship (i.e. their relative weight in the
indexes) among those three anthropometric measures. BMI rose from 22.6 (cohorts 193438) to 23.2 (cohorts 1944-48) and decreased among subsequent cohort groups as a result
of the strong increase in mean cohort height. RI decreased from 16.6 (cohorts 1934-38) to
13.7 units (cohorts 1944-48) thus indicating an increase in robustness related to a limited
progress in stature and proportionally higher increments in weight and CC. This trend
was reversed among cohorts born since 1949 as the result of the dramatic increase in
height observed during the second half of the 20th century. Such increase was not
paralleled by CC that remained stable or slightly decreased (Table 2).
12
Table 2
Anthropometric measures and composite indexes
Spanish male cohorts born 1934-73
Cohorts
1934-38
1939-43
1944-48
1949-53
1954-58
1959-63
1964-68
1969-73
Height
166.4
167.2
168
169.4
170.9
172.2
173.8
175
Weight
62.5
64
65.5
66.1
66.6
67
67.3
69.1
CC
87.2
87.9
88.8
88.8
88.9
89.1
88
BMI
22.6
22.9
23.2
23
22.8
22.6
22.3
22.5
RI
16.6
15.3
13.7
14.5
15.3
16.1
18.5
Source: Own computations based on Military Statistics of Spanish Yearbooks
The anthropometric map of Spain became progressively more homogeneous over
the life courses of the aforementioned cohorts. For instance, height differences between
the tallest (región Vasca) and the shortest (región Andaluza) among older cohorts were
about 4 cm. These differences more than halved among cohorts born at the beginning of
the 1970s (less than 2 cm. between the tallest –región Aragonesa-riojana— and the
shortest at the time –región Galaica-) (Figure 3). The variation coefficients of regional
heights shifted from 0.009 to 0.004 alongside. Therefore, short regions grew more than
tall regions during the central decades of the 20th century. Regional differences in mean
weight also lessened. The average weight among cohorts born 1934-38 ranged from 60.5
kg (región Andaluza) and 67.0 kg (región Vasca) whereas among those born 1969-73
they ranged from 68.8 kg (región Catalana) and 70 kg (región Aragonesa-riojana). This
caused BMI and RI to converge across regions as displayed by their respective variation
coefficients (BMI shifted from 0.024 to 0.009 and RI did so from 0.122 to 0.053 among
cohorts born 1934-38 and 1964-68 respectively) (Appendix, Table A5).
13
Figure 3
Spatial patterns
Male cohorts 1934-73
Height
1934-38
(Spain 166.40 cm)
1954-58
(Spain 170.89 cm)
1964-68
(Spain 173.67 cm)
(Spain 22.6 kg/m2)
BMI
(Spain 22.8 kg/m2)
(Spain 22.3 kg/m2)
(Spain 16.6 units)
RI
(Spain 15.3 units)
(Spain 18.5 units)
Source: Own computations based on Military Statistics of Spanish Yearbooks
Note. All regions fall in the height interval 174-176 among the younger cohorts (1969-73). We opted to
maintain the same intervals over time as we are interested in showing both the general trend in cohort
height and the convergence across regions. In the case of BMI this convergence happened as this index was
decreasing as a result of the strong increase in height. Remember that the downturn in RI indicates the rise
of robustness (colors on the map were set to point in the same direction: the darker, the taller and the more
robust)
14
The reduction of anthropometric disparities in height was already happening
among cohorts born during the 1940s. This is illustrated by the relatively higher growth
of Central-Southern regions with respect to North-Eastern regions. This process
noticeably intensified among cohorts born during the 1950s and the 1960s which is in
accordance with an effective reduction of economic disparities. These disparities,
nevertheless, remained significantly higher than anthropometric disparities (Table 3 and
Figures 4 and 5).
15
Table 3
Inter-cohort height changes (relative deviations from the national trend)
Region
SPAIN
1939-43
0.50%
1949-53
Rank
0.82%
1959-63
Rank
0.76%
1969-73
Rank
0.70%
Rank
AND
0.12
2
-0.09
7
0.06
1
0.25
4
ARA-RIO
-0.12
6
-0.07
6
-0.06
5
0.27
3
CAN
-0.15
8
-0.26
9
-0.08
7
-0.2
10
CANT
0.05
3
-0.28
10
-0.29
11
-0.02
8
CAT
-0.14
7
-0.13
8
-0.19
9
-0.07
9
CyL
-0.04
4
0.16
2
-0.03
4
0.28
2
EXT-MAN
-0.06
5
0.09
3
0.01
3
0.18
5
GAL
-0.22
11
0.02
5
0.06
2
0.3
1
LEV
-0.17
10
0.08
4
-0.07
6
-0.34
11
MAD
0.24
1
0.17
1
-0.13
8
0.09
6
PV
-0.17
9
-0.38
11
-0.23
10
0.05
7
Source: Own computations based on Military Statistics of Spanish Yearbooks
Note. The first column contains the deviation from the national growth rate in percent points between two
successive cohort groups. The national rate is on the first row and it was computed as a rate of change
between two cohort groups. For instance, 0.50 percent in the first row is the delta between the cohort
groups 1934-38 and 1939-43. The value 0.12 on the second row for Andalusia (AND) means that this
region progressed 0.62 percent over the same period.
16
Figure 4
Cohort height (cm) and cohort RI in six Spanish regions
Height
Robustness Index
10.00
12.00
14.00
16.00
18.00
20.00
22.00
1934-38
1939-43
ARA-RIO
1944-48
CAN
1949-53
CyL
CAT
1954-58
1959-63
EXT-MAN
1964-68
GAL
SPAIN
Source: Own computations based on Military Statistics of Spanish Yearbooks
17
Figure 5
Variation coefficients
1.0000
VC
0.1000
0.0100
0.0010
1934-38 1939-43 1944-48 1949-53 1954-58 1959-63 1964-68 1969-73
Cohort/period
Height
RI
m0
p.c. GDP
Source: Own computations based on Military Statistics of Spanish Yearbooks
Despite this convergence across regions, spatial patterns were very persistent. A
North-Eastern arch of tall and robust regions compares to a group of short and weedy
Central-Southern regions. This pattern disappeared for BMI but it was still observed for
stature and RI among cohorts born at the end of the 1960s (this was displayed in Figure
3).
In terms of height, some regions kept their advantage over the whole period
analyzed. This is the case of the region Catalana (Catalonia and Balearic Islands) the
region Vasca (Basque Country) the Canary Islands and Madrid. Likewise the South
remained as a compact group of regions below the national average. Few regions gained
positions in an ordinal ranking of the indicators over the course of the twentieth century.
Castille-Leon is an exception. This region began to diverge from the short-averaged
regions since the middle of the 1940s and by the 1960s its mean stature was already
above the average. On the contrary, the región Levantina (on the East coast) lost position
and settled below the average in the 1970s along with the short regions. Finally, the
progress of the región Aragonesa-riojana is outstanding since it rose to the first place in
height and also ranked among the top-five regions in RI at the end of the analyzed period.
18
These anthropometric patterns that basically reflect the nutritional status of the
population are only partly related to the economic performance of regions as
approximated by GDP and their sanitary context as approximated by infant mortality.
Between 1930 and 1970 the regional GDP displayed few variations. Madrid and the
North-Eastern regions consistently ranked at the top. With few exceptions (i.e. Madrid
and the poorer regions of the North-Eastern arch) infant mortality was also lower in those
regions (Table 4). Madrid, an urban region located in the center of the country had high
GDP and high infant mortality levels during the central decades of the twentieth century.
This region was probably affected by an urban penalty until improved sanitation and
hygiene conventions and facilities were spread in subsequent phases of the urbanization
process. Illustratively, by the middle of the 1970s Madrid was already among the regions
with lower infant mortality rate.
Region
Table 4
Per capita GDP (current prices) and m0
(Spain=100)
GDP
1930
1950
1970
1934-38
76.4 9
72.5 9
72.5 10
105.7 9
m0
1949-53
1969-73
98.3 6
111.6 8
ARA-RIO
112 4
110.03 5
108.9 4
92.8 6
101.7 8
94.3 5
CAN
92.1 7
83.2 8
85.2 7
98.2 8
99.3 7
95.2 6
CANT
100.45 5
114.3 4
105.4 5
81.7 3
85.5 4
102.3 7
CAT
148.75 2
138.9 3
133.2 2
64.1 1
72.4 1
77.2 1
CyL
89.7 8
92.6 6
83.5 8
126 11
131.3 11
118.2 9
66.55 11
66.9 11
64.8 11
124.6 10
118.7 10
123.3 10
74.7 10
72.1 10
78.8 9
90.1 5
110.2 9
133.8 11
LEV
92.4 6
89.95 7
91.75 6
82.3 4
80.9 3
91.9 4
MAD
145.7 3
148.3 2
132.9 3
96.1 7
91.1 5
88.1 2
AND
EXT-MAN
GAL
161.2 1
181.6 1
142 1
70.5 2
73.4 2
91.6 3
PV
Source: Own computations based on Military Statistics of Spanish Yearbooks as explained in the section
entitled Methods. Absolute numbers are provided on Table A4 in the Appendix.
19
Short-averaged regions display relatively low GDPs and relatively high infant
mortality levels but this association is notoriously ambiguous among tall regions. For
instance, the Canary Islands were historically tall-averaged but relatively low-averaged in
terms of GDP. Moreover, its mortality levels were close to the national average so they
may be considered high relative to the group of tall regions (e.g. the región Catalana and
the región Vasca). It must be noted that tall regions ranged broadly in terms of infant
mortality (during the 1930s, m0 in the Canary Islands and Madrid was over 120 per
thousand whereas it was 91 and 82 per thousand in the region Vasca and the región
Catalana respectively12). Robustness partly resolves those paradoxes in that it sets the
Canary Islands with the less-developed regions (i.e. poorly nourished) and Madrid with
the high-infant mortality regions during the first stage of the modern process of
urbanization.
Yet some discrepancies between economic and anthropometric indicators persist
in that the robust North-Eastern arch (presumably well-nourished) includes relatively
short and/or relatively poor regions like Galicia and Castille-Leon. This is not the case for
less robust Spain made up of Central-Southern regions (presumably poorly nourished and
relatively poor with the exception of Madrid).
Discussion
In this work trends and patterns of height and robustness in Spain have been
analyzed during the main phase of modern socioeconomic development in this country
(i.e. the central decades of the twentieth century).
Trends in cohort height indicate substantial improvements in the nutritional status
of the Spanish (male) population during that period. This has been observed even among
cohorts that were exposed to war and post-war related hardships.
Trends in robustness as approached by BMI and RI have a double interpretation.
In a first stage (cohorts born during the 1930s and the 1940s) these indexes indicate an
increase in robustness that technically has to do with a modest progress of height at the
time that weight and CC were meaningfully increasing. The opposite occurred among
12
The latter has mainly to do with the very low infant mortality rates in the Balearic Islands, 72.3 per
thousand in 1934-38 (Gómez-Redondo, 1992).
20
subsequent cohorts whereby less robust bodies are likely to reflect better nourished and
healthier individuals.
This anthropometric picture was framed by cross-regional convergence and
persistent spatial patterns.
A convergence between tall-robust (well-nourished) and short-weak (poorly
nourished) regions is observed. Convergence was particularly strong for cohorts born
between 1950 and 1960. This period witnessed the end of autarchic policies and the end
of the economic isolation of Spain. Yet the initial disparities observed across regions (i.e.
among cohorts born during the 1930s) cannot be explained merely through assumptions
of previous hardships. Rather those disparities were the result of a long-term process of
height differentiation that might have had its origin during the second half of the
nineteenth century. That process would have consolidated during the first decades of the
twentieth century since regions appeared in a very similar ordinal ranking among cohorts
born 1875-1934 in a nationally representative sample of recruits (Quiroga, 1998 and
2001). The regional ranking of statures until the middle of the twentieth century remained
almost invariably headed by the Basque Country, Catalonia and the Canary Islands.
Furthermore, the rest of positions in the list also remained very stable with few
exceptions (e.g. those born in Andalusia during the last third of the nineteenth Century
were on an intermediate position so that cohorts born during the first decades of the
twentieth Century relatively shrank and set the region among the shortest)13.
The range of height differentials deserves some attention. That was estimated to
be above 6 cm. among cohorts 1875-1934 which is close to that observed among those
enlisted in 1924 (born at the beginning of the twentieth century) which were about 4.5 cm
between the Basque (the tallest) and those enlisted in Galicia and La Rioja (the shortest at
that time) (Quiroga, 2001). In the main this agrees with our results for male cohorts born
during the 1930s. In consequence, after a process of divergence during the second half of
the nineteenth century differences would have leveled off during the first decades of the
13
This agrees with the studies in economic history that have prompted the trajectory followed by Andalusia
from its second place among the industrials regions (only behind Catalonia) by the middle of the 19th
century to be among the most delayed regions on the eve of the Spanish Civil War (1936-39) (an overview
of these studies in Martínez-Carrión, 2005).
21
twentieth century and they would have decreased thereafter particularly among cohorts
born since the 1950s.
This convergence across regions must be interpreted in generational terms by
analyzing both the energy inputs (intakes) and outputs (expenditure) that influence the
nutritional status of the population. Regarding the inputs, Spanish cohorts born during the
second half of the twentieth century grew up in a context of relative food security (stock
and access were met although dietary quality was improvable in an initial stage). Spain
overcame structural scarcity during the 1950s and this was followed by a diversification
of foodstuffs during the 1960s and the 1970s thus going across the patterns of the
nutritional transition (Popkin, 1993; Cussó, 2005). Meanwhile potential energy outputrelated disruptions were dramatically reduced in that hygiene measures and sanitary
provisions were substantially improved. These factors endorsed the health transition
process at least until the decade of the 1980s (Spijker et al., 2012).
In our view, these shifts in the components of the net nutritional status of a
population cannot be dissociated from the Spanish economic take-off during the second
half of the twentieth century but anthropometrics are not in total accordance with either
the geography of income or the economic trajectories followed by the regions. Poor
regions caught up in terms of height and robustness more successfully than in economic
terms as income disparities remained relatively large over the analyzed period. The
anthropometric convergence seem to us even more relevant given the absence of specific
policies aiming at correcting socioeconomic disparities across the country (those policies
were not effectively implemented until the arrival of democracy in the late 1970s; GarcíaBallesteros, 1990). Nevertheless, the convergence hardly modified an ordinal ranking of
the spatial pattern. In terms of stature, 3 out of 4 regions initially at the bottom (i.e.
cohorts born during the 1930s) remained at those positions during the 1970s (it must be
noted that those cohorts grew up during the 1980s and the 1990s).
Finally, some discrepancies found between height patterns and robustness patterns
are worth commenting on. That tall but skinny regions are found along with short but
robust regions in Spain may be explained by relatively good diet combined with some
other high impact environmental stressors or growth disruptors (e.g. sanitary conditions
as approximated by infant mortality). In our view this leads to the necessity to interpret
22
trends in height in light of other anthropometric measures when approaching the
biological components of living standards.
Southern regions like Andalusia and the región Extremeño-manchega were
systematically poor, short and less robust during most of the twentieth century.
Interestingly, this set of regions coincides with those whose relative per capita GDP
decreased in the long run (Carreras, 1990).
By contrast, the robust Spain (presumably well-nourished) spread on a NorthEastern arch of regions from Galicia (on the far North-West) to the East coast (current
region Comunitat Valenciana) that was to some extent independent from both height
scores and economic development. Among Northern Spaniards both relatively tall (e.g.
Basque) and relatively short populations (i.e. Galician) are found but all of them were
significantly more robust on average than Southern Spaniards. In an examination of their
robustness, regions like Galicia and Castille-Leon were not as disadvantaged as would
have been concluded in an analysis of height alone. Northern robustness (shared by
economically developed and underdeveloped regions) was probably associated with a
better provision and/or an easier access to high protein and caloric foodstuffs such as
meat and milk. In 1910-12 that arch of robust regions very much coincided with food
prices above the national average but also with cheaper meat and dairy products among
the Spanish provinces. By contrast, Southern provinces displayed an apparent advantage
regarding the prices of cereals and fats (i.e. olive oil; Nicolau and Pujol, 2006). These
authors concluded that these differentials were indicative of the actual consumption and
that Northern provinces had generally easier access to high protein and caloric foodstuffs
than inner and southern provinces had. Along with Simpson we hypothesize that meat
and dairy products remained rare in these areas until well into the second half of the
century. This supposition has several explanations none of which are mutually exclusive:
the historical agricultural specialization by region, the physical constraints to the
development of mixed agrarian systems, the limited demand from urban markets and the
poor market integration of the country (Simpson, 1995). Simpson argues that ‘from the
turn of the nineteenth century onwards, the decline in rural industry and the increasing
penetration of cereals from the Interior [i.e. inner regions] encouraged greater livestock
specialization in the North […] The North had 7.3 per cent of the agricultural land area,
23
but 36 per cent of livestock output in 1929-33’ (1995: 191-192). Furthermore, an
estimated food cost index adjusted by wages among twelve Spanish provinces in different
regions uncovered systematically higher costs for a set of basic foodstuffs in the Southern
and inner provinces (Ballesteros, 1997). This evidence is also in accordance with the
variation in the market price of high protein products across regions. For instance milk’s
prices per liter in 1933 were 0.42 pesetas in the North (regions of Galicia, Asturias,
Cantabria and the Basque Country, 0.52 in Castille-Leon, 0.50 in the Ebro valley (region
Aragonesa-Riojana), 0.53 in the Mediterranean East Coast, 0.60 in the region ExtremeñoManchega and 0.73 in Andalusia) (Simpson, 1995: 194). This very much agrees with
disparities in robustness that our results have displayed.
The Canary Islands are another interesting case. Any hypothetical environmental
advantage attributed to this region in light of its tallness should be questioned in light of
our outcomes. Males enlisted in the Canary Islands were tall but not robust which drives
us to think about more than just environmental conditions in order to explain their above
average height (e.g. ethnic specificities; Hooton, 1925)14. Furthermore infant mortality
for the Canary Islands was among the highest in Spain at the beginning of the twentieth
Century. Thus height cannot easily be related to low morbidity exposure, at least not
during that critical period of physical growth.
Some of these findings need to be interpreted with caution. Tall-averaged regions
like the Basque Country, Catalonia or Madrid were also the most developed as reflected
by industrialization and urbanization levels as well as by per capita income. They were
also the main destinations of internal migration flows. Within Spain, these flows were
intense during the 1950s and the 1960s (García-Barbancho and Delgado-Cabeza, 1988)
and they might imply selection effects thus affecting some of the anthropometric trends
and patterns. Regarding the anthropometric convergence across regions the most
disturbing bias would result from systematically shorter migrants (shorter than nonmigrants in their home region and shorter than natives in the destination region). In such
a case, migration would partly explain those trends but such a statement contradicts the
hypothesis of a selective migration. Contrarily, if migrants were systematically taller than
14
A series of unpublished papers by Cándido Róman argue in favor of environmental advantages and
particular food properties to explain the tallness in these islands. Results, nevertheless, do not seem
concluding in that direction.
24
non-migrants and/or taller than the natives at destination, that might cause anthropometric
disparities across regions to increase artificially (i.e. aside from the environmental
conditions during infancy and adolescence). The cohort trends that have been displayed
in this work do not necessarily point to a systematic bias caused by selective migration
but this effect cannot be totally discarded. The anthropometric convergence started very
early but it was particularly strong among those cohorts born during the 1950s and 1960s.
These cohorts attained their adult height between the 1970s and 1980s once migration
flows had moderated. By contrast, cohorts born during the 1930s and the 1940s
potentially featured the most intense flows. In consequence, the initial disparities as well
as the slow pace of convergence among those cohorts might have partly to do with the
aforementioned selective effect. Notwithstanding, regions like Castille-Leon experienced
an outstanding progress in height that spanned among cohorts born 1940-70 and
essentially ceased their growth between 1970 and 1990. Over this period the intensity and
even the net result of migratory flows in that and other regions varied whereas the
progress of height and robustness was rather continuous.
With regard to the issue of migration is unfortunate that few and very partial
sources are available in Spain. Some military records provide the province of enlistment
and the province of birth but this is not enough to disentangle migration and
environmental effects since the time of migration is unknown. In consequence, it is
ignored to what extent migrants’ advantage (if any) would be a result of selection in
origin or successful adaptation in the destination place (i.e. favored by an improved
environment).
25
References
Abella, Fermín. 1915. Manual de Quintas. Madrid, Imprenta de El Consultor
Alcaide, Julio. 2003. Evolución económica de las regiones y provincias españolas en el
siglo XX. Bilbao, BBVA.
Ballesteros, Esmeralda (1997): “Una estimación del coste de la vida en España, 18611936”. Revista de Historia Económica, 15 (2), pp. 363-395.
Bogin, Barry, 1988. Patterns of Human Growth. Cambridge: Cambridge University
Press.
Cámara, Antonio D., Joan García-Román. 2010. Ciclos largos de nivel de vida biológico
en España (1750–1950): propuesta metodológica y evidencias locales. Investigaciones en
Historia Económica 17: 95-118.
Carreras, Albert. 1990. Fuentes y datos para el anàlisis regional de la industrialización
española, in Jordi Nadal and Albert Carreras (dirs), Pautas regionales de la
industrialización española (siglos XIX y XX). Barcelona: Ariel: 3-20.
Carreras, Albert, Leandro Prados de la Escosura, Joan R. Rosés. 2005. Renta y riqueza, in
Albert Carreras and Xavier Tafunell (eds.), Estadísticas Históricas de España. Siglos XIX
y XX, second ed. Madrid: Fundación BBVA: 1298-1376.
Cussó, Xavier. 2005. El estado nutritivo de la población española, 1900-1970. Análisis de
las necesidades y disponibilidades de nutrientes. Historia Agraria, 36: 329-358.
Escudero, Antonio, Hipólito Simón. 2003. “El bienestar en España: una perspectiva de
largo plazo (1850-1991)”. Revista de Historia Económica, 21(3) pp. 525-565.
García-Barbancho, Alfonso, Manuel Delgado-Cabeza. 1988. Los movimientos
migratorios interregionales en Espana desde 1960. Papeles de Economía Española, 34:
241-266.
García-Ballesteros, Aurora. 1990. Desequilibrios interterritoriales en la España de las
autonomías. Boletín de la Asociación de Geógrafos Españoles, 11: 1-14.
Gómez-Mendoza, Antonio, Vicente Pérez Moreda. 1985. Estatura y nivel de vida en la
España del primer tercio del siglo XX. Moneda y Crédito 174: 29-64.
Gómez-Redondo, Rosa (1992): La mortalidad infantil española en el siglo XX. Madrid:
C.I.S.-Siglo XXI
González-Portilla, Manuel. 1998. Tallas, crecimiento económico y desequilibrios
regionales en España. In VV staff, Los 98 Ibéricos y el mar. Salamanca: Sociedad Estatal
Lisboa 98, Issue IV La sociedad y la economía en la Península Ibérica: 85-108.
26
González Portilla, M. 2001. Talla, nutrición y desarrollo en España: análisis regional
(1850-1900). En VV staff, Las claves de la España del siglo XX. Madrid: Sociedad
Estatal España Nuevo Milenio, issue VII, Las transformaciones económicas: 185-203.
Guillén-Rodríguez, Mateo. Online. La estadística de Reemplazo y Reclutamiento de los
Ejércitos. INE http://www.ine.es/revistas/estaespa/3_7.pdf [05/01/2012]
Hatton, Timothy J, Bernice E. Bray. 2010. Long run trends in the heights of European
men, 19th–20th centuries. Economics and Human Biology 8: 405-413.
Hoyos-Sainz, Luis. 1942. Antropodemografía española. Regiones y razas. Madrid: Real
Sociedad Geográfica.
Hooton, Earnest, A. 1925. The Ancient Inhabitants of the Canary Islands. Harvard,
Harvard University Peabody Museum.
IHDI
(International
Human
Development
indicators).
http://hdrstats.undp.org/en/countries/profiles/ESP.html [05/01/2012]
Online
INE (Instituto Nacional de Estadística). 1991. Anuario Estadístico de España 1990.
Madrid: INE.
INE (Instituto Nacional de Estadística), 2007. Anuario Estadístico de España 2007.
Madrid: INE.
INE (Instituto Nacional de Estadística). Online. Series of vital statistics from 1941 and
historical vital registers at INEbase/Historia [05/01/2012].
Komlos, John, Marieluise Baur. 2004. From the tallest to (one of) the fattest: the
enigmatic fate of the American population in the 20th Century. Economics and Human
Biology 2: 57-74
Livi-Bacci, Massimo. 1992. A Concise History of World Population. Cambridge, USA:
Blackwell Publishers.
Martínez-Carrión, José M. 1994. Niveles de vida y desarrollo económico en la España
contemporánea: una visión antropométrica. Revista de Historia Económica, 12: 685-716.
Martínez-Carrión, José M. 2001. Estatura, salud y bienestar en las primeras etapas del
crecimiento económico español. Una perspectiva comparada de los niveles de vida.
AEHE working paper series 0102.
Martínez-Carrión, José M. 2005. Estaturas, desigualdad regional y desarrollo económico
en Italia y España durante el siglo XX. Mediterráneo Económico, 7.
27
Nicolau, Roser, Josep Pujol. 2006. Variaciones regionales de los precios de consumo y de
las dietas en España, en los inicios de la transición demográfica. Revista de Historia
Económica. Journal of Iberian and Latin American Economic History, 24 (3): 521-554.
Popkin, Barry M. 1993. Nutritional Patterns and Transitions. Population and
Development Review, 19 (1): 138-157.
Quiroga, Gloria. 1998. Height evolution in Spain, 1893-1954. An analysis by regions and
professions, in John Komlos and Joerg Baten (eds.): The biological standard of living in
comparative perspective. Stuttgart: Franz Steiner: 359-383.
Quiroga, Gloria. 2001. Estatura, diferencias regionales y sociales y niveles de vida en
España (1893-1954). Revista de Historia Económica, 19 (1); 175-200.
Reher, David S. 2001. In search of the ‘urban penalty’: exploring urban and rural
mortality patterns in Spain during the demographic transition. International Journal of
Population Geography 7: 105–127.
Simpson, James. 1995. Spanish agriculture: the long siesta, 1765-1965. Cambridge:
Cambridge University Press.
Spijker, Jeroen J., Antonio D. Cámara, Amand Blanes. 2012 (in press). The health
transition and biological living standards: adult height and mortality in 20th-century
Spain. Economics and Human Biology.
Tanner, James M. 1989. Foetus into Man: physical growth from conception to maturity.
Harvard: Harvard University Press.
28
Appendix
Table A1
Average height in Spain and its regions
Cohorts born 1934-73
Region
AND
ARA-RIO
CAN
CANT
CAT
CyL
EXT-MAN
GAL
LEV
MAD
PV
SPAIN
1934-38
165.34 11
167.18
6
168.18
3
167.43
4
165.62
8
168.72
2
165.43 10
165.52
9
166.97
7
167.39
5
169.64
1
166.35
1939-1943
166.36
167.81
168.77
168.35
166.38
169.32
166.16
165.98
167.51
168.62
170.20
167.18
1944-1948
167.10
168.59
169.67
169.16
167.26
170.14
167.04
166.90
168.25
169.63
170.96
168.61
9
6
3
5
8
2
10
11
7
4
1
9
6
3
5
8
2
10
11
7
4
1
1949-1953
168.33
169.86
170.62
170.07
168.87
171.31
168.56
168.31
169.77
171.31
171.72
169.88
10
6
4
5
8
3
9
11
7
2
1
1954-1958
169.86
171.34
171.65
171.39
170.50
172.15
170.07
169.76
171.12
172.39
172.55
170.89
10
6
4
5
8
3
9
11
7
2
1
1959-1963
171.25
172.54
172.81
172.18
171.74
173.12
171.38
171.15
172.31
173.47
173.46
172.18
10
5
4
7
8
3
9
11
6
1
2
1964-1968
172.78
174.29
174.53
173.93
173.73
174.32
172.98
172.58
173.86
174.57
174.58
173.85
10
5
3
6
8
4
9
11
7
2
1
1969-1973
174.42
175.99
175.39
175.12
175.44
175.42
174.50
174.30
174.49
175.94
175.90
175.07
10
1
6
7
4
5
8
11
9
2
3
Source: Own computations based on Military Statistics on Spanish Yearbooks. The second column for each
cohort group indicate the ranking among regions
Table A2
Average weight in Spain and its regions
Cohorts born 1934-73
Region
AND
ARA-RIO
CAN
CANT
CAT
CyL
EXT-MAN
GAL
LEV
MAD
PV
SPAIN
1934-38
60.54 11
64.36
4
62.64
8
65.58
2
63.12
7
64.91
3
60.77 10
64.30
5
63.23
6
61.79
9
67.05
1
62.54
1939-1943
62.31
65.50
63.83
67.00
64.20
66.32
62.18
65.34
64.48
63.66
67.98
64.03
10
4
8
2
7
3
11
5
6
9
1
1944-1948
63.93
66.79
64.91
68.21
65.42
67.51
63.80
66.62
65.83
65.62
69.68
65.51
10
4
9
2
8
3
11
5
6
7
1
1949-1953
64.77
67.27
65.72
68.71
65.84
67.64
64.67
67.05
66.44
66.41
69.93
66.77
10
4
9
2
8
3
11
5
6
7
1
1954-1958
65.46
67.55
65.93
68.28
66.09
67.69
65.33
67.42
67.03
66.76
69.24
66.61
10
4
9
2
8
3
11
5
6
7
1
1959-1963
66.02
67.75
65.94
68.27
66.44
67.38
65.91
67.47
67.51
67.71
68.44
66.97
9
3
10
2
8
7
11
6
5
4
1
1964-1968
66.57
68.11
66.46
67.92
66.84
67.20
66.58
67.27
67.52
67.52
68.03
67.35
10
1
11
3
8
7
9
6
5
4
2
1969-1973
69.13
69.96
68.20
69.39
68.91
68.78
69.11
69.00
69.03
69.44
69.68
69.13
5
1
11
4
9
10
6
8
7
3
2
1964-1968
87.52
89.34
87.36
88.52
87.85
88.26
87.98
87.82
87.69
88.58
88.64
88.01
10
1
11
4
7
5
6
8
9
3
2
Source: Own computations based on Military Statistics on Spanish Yearbooks
Table A3
Average chest circumference in Spain and its regions
Cohorts born 1934-73
Region
AND
ARA-RIO
CAN
CANT
CAT
CyL
EXT-MAN
GAL
LEV
MAD
PV
SPAIN
1934-38
86.33
87.98
87.24
88.41
87.14
88.12
86.64
87.37
87.55
87.36
89.33
87.23
11
4
8
2
9
3
10
6
5
7
1
1939-1943
87.15
88.51
88.21
88.75
87.71
88.75
87.21
87.87
88.17
88.85
89.63
87.89
11
5
6
3
9
4
10
8
7
2
1
1944-1948
88.28
89.19
88.95
89.78
88.58
89.69
88.10
88.72
88.96
89.76
90.38
88.84
10
5
7
2
9
4
11
8
6
3
1
1949-1953
87.93
88.81
87.98
89.57
88.05
89.57
87.59
88.34
88.35
89.08
89.56
88.83
10
5
9
1
8
2
11
7
6
4
3
1954-1958
88.19
89.17
88.52
89.66
88.80
89.86
88.40
88.76
89.05
89.59
90.06
88.95
11
5
9
3
7
2
10
8
6
4
1
1959-1963
88.46
89.97
88.08
89.56
88.87
89.80
88.56
88.99
89.25
89.64
89.59
89.08
10
1
11
5
8
2
9
7
6
3
4
Source: Own computations based on Military Statistics on Spanish Yearbooks
29
Table A4
Per capita GDP (current prices; million of pesetas) and infant mortality rates (per thousand)
GDP
Region
m0
1935-40
1950-55
1970-75
1934-38
1949-53
1969-73
AND
1576
8448
98174
136.81
70.75
31.96
ARA-RIO
2236
12824
143168
120.1
73.18
27.01
CAN
1893
9829
117661
127.16
71.45
27.28
CANT
2224
13431
137402
105.69
61.49
29.3
CAT
3292
18840
177980
82.92
52.06
22.12
CyL
1823
10630
112567
163.09
94.48
33.85
EXT-MAN
1386
8066
91335
161.24
85.43
35.32
GAL
1529
8625
102549
116.63
79.27
38.32
LEV
2102
12016
132944
106.58
58.22
26.34
MAD
3176
18168
183572
124.37
65.53
25.24
PV
3473
21761
184973
91.23
52.81
26.26
Source: Own computations on data from Alcaide (2003) and Gómez-Redondo (1992)
Table A5
Variation coefficients
Period
Height
1934-38
0.0093
1939-43
0.0088
1944-48
0.0087
1949-53
0.0072
1954-58
0.0058
1959-63
0.0048
1964-68
0.0041
1969-73
0.0037
-56.3
Change (percent)
Weight
0.0342
0.0299
0.0282
0.0224
0.0183
0.0136
0.0086
CC
0.0101
0.0091
0.0083
0.0082
0.0069
0.0066
0.0065
BMI
0.0237
0.0212
0.0195
0.0171
0.0142
0.0117
0.0088
RI
0.1222
0.1121
0.1187
0.107
0.0832
0.0747
0.0528
-74.72
-35
-62.8
-56.8
m0
0.198
p.c. GDP
0.346
0.18
0.374
0.165
-16.3
0.242
-30
Source: Own computations based on Military Statistics on Spanish Yearbooks
Table A6
Missing anthropometric data (percent) as reported in the Military Statistics
Cohort 1971
Cohort 1970
Region
Height
Weight
Region
CC
Height
AND
7.9
7.9
99.2
AND
ARA-RIO
5.7
5.7
98.2
ARA-RIO
Cohort 1973
Weight
4.9
CC
Region
Height
4.9
14.5
AND
4.8
4.8
24.4
14.1
13.9
43.1
Weight
CC
4.4
4.4
14
ARA-RIO
4.2
4.2
10.5
CAN
15.1
15
46.2
11.6
CAN
20.5
20.2
97.6
CAN
CANT
7.5
7.7
99.3
CANT
4.6
4.7
14.3
CANT
1.4
2.4
CAT
8.9
9
96.2
CAT
4
4
9.4
CAT
3.7
3.7
8.3
CyL
11.4
11.3
82.7
CyL
11.9
11.8
42.6
CyL
13.4
13.2
39.1
EXT-MAN
10.3
10.2
98.9
EXT-MAN
6.6
6.5
19
EXT-MAN
4.7
4.6
14
GAL
12.2
12.2
90.1
GAL
12.5
12.4
21
GAL
10.3
10.3
17.6
LEV
7.5
7.6
97.4
LEV
5.9
5.9
19.3
LEV
3.6
4
15.5
MAD
78.7
78.8
99.7
MAD
13.2
13.2
33.3
MAD
16.7
16.8
31.7
PV
24.6
24.4
99
PV
17.7
17.6
59.7
PV
13.9
13.7
57.3
SPAIN
20.9
20.9
95.1
SPAIN
9.1
9.1
27.6
SPAIN
8.9
8.9
24.9
Source: Military Statistics on Spanish Yearbooks
Note. No regional data is available for the cohort 1972 that was not included in the analysis. The missing percent for Spain within that
cohort were 9.1, 9.1 and 27.6 respectively.
30